Optimal combination of feature selection and classification via local hyperplane based learning strategy

摘要

BackgroundClassifying cancers by gene selection is among the most important and challenging procedures in biomedicine. A major challenge is to design an effective method that eliminates irrelevant, redundant, or noisy genes from the classification, while retaining all of the highly discriminative genes.